Current AI technologies are rule-based systems that utilize Bayesian networks or multi-objective optimization techniques to completely map out the possible decision space and provide the best answer. For instance, AI software that has been trained to play chess maps out all of the possible allowed moves and attempts to select the optimal next move based on the current state of the pieces in the game. However, these techniques do not map disallowed states. This strict adherence to rules makes current AI approaches suboptimal, or even dangerous, for certain applications. Accordingly, an improved approach may be beneficial.